A typical task assignment system algorithmically assigns tasks arriving at the task assignment center to agents available to handle those tasks. At times, the task assignment system may have agents available and waiting for assignment to tasks. At other times, the task assignment center may have tasks waiting in one or more queues for an agent to become available for assignment.
In some typical task assignment centers, tasks are assigned to agents ordered based on time of arrival, and agents receive tasks ordered based on the time when those agents became available. This strategy may be referred to as a “first-in, first-out,” “FIFO,” or “round-robin” strategy. For example, in an “L2” environment, multiple tasks are waiting in a queue for assignment to an agent. When an agent becomes available, the task at the head of the queue would be selected for assignment to the agent.
Some task assignment systems prioritize some types of tasks ahead of other types of tasks. For example, some tasks may be high-priority tasks, while other tasks are low-priority tasks. Under a FIFO strategy, high-priority tasks will be assigned ahead of low-priority tasks. In some situations, some low-priority tasks may have a high average waiting time while high-priority tasks are handled instead. Moreover, agents that might have handled low-priority tasks more efficiently may end up being assigned to high-priority tasks instead, leading to suboptimal overall performance in the task assignment system.
In view of the foregoing, it may be understood that there may be a need for a system that efficiently optimizes the application of a BP strategy in L2 environments of a task assignment system.